RU2010110954A - EFFECTIVE CALCULATION OF WEIGHT FILTER FACTORS FOR MIMO SYSTEM - Google Patents

EFFECTIVE CALCULATION OF WEIGHT FILTER FACTORS FOR MIMO SYSTEM Download PDF

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RU2010110954A
RU2010110954A RU2010110954/07A RU2010110954A RU2010110954A RU 2010110954 A RU2010110954 A RU 2010110954A RU 2010110954/07 A RU2010110954/07 A RU 2010110954/07A RU 2010110954 A RU2010110954 A RU 2010110954A RU 2010110954 A RU2010110954 A RU 2010110954A
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Стивен Дж. ГОВАРД (US)
Стивен Дж. ГОВАРД
Джон В. КЕТЧУМ (US)
Джон В. Кетчум
Марк С. УОЛЛЭЙС (US)
Марк С. УОЛЛЭЙС
Питер МОНСЕН (US)
Питер МОНСЕН
Джей Родни УОЛТОН (US)
Джей Родни УОЛТОН
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Квэлкомм Инкорпорейтед (US)
Квэлкомм Инкорпорейтед
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/0413—MIMO systems
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/08—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station
    • H04B7/0837—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station using pre-detection combining
    • H04B7/0842—Weighted combining
    • H04B7/0848—Joint weighting
    • H04B7/0854—Joint weighting using error minimizing algorithms, e.g. minimum mean squared error [MMSE], "cross-correlation" or matrix inversion
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/02—Arrangements for detecting or preventing errors in the information received by diversity reception
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/0202—Channel estimation
    • H04L25/024—Channel estimation channel estimation algorithms
    • H04L25/0242—Channel estimation channel estimation algorithms using matrix methods
    • H04L25/0248—Eigen-space methods
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
    • H04L25/03006—Arrangements for removing intersymbol interference
    • H04L2025/0335—Arrangements for removing intersymbol interference characterised by the type of transmission
    • H04L2025/03426—Arrangements for removing intersymbol interference characterised by the type of transmission transmission using multiple-input and multiple-output channels
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
    • H04L25/03006—Arrangements for removing intersymbol interference
    • H04L2025/03592—Adaptation methods
    • H04L2025/03598—Algorithms
    • H04L2025/03605—Block algorithms
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
    • H04L25/03006—Arrangements for removing intersymbol interference
    • H04L2025/03592—Adaptation methods
    • H04L2025/03598—Algorithms
    • H04L2025/03611—Iterative algorithms
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/0202—Channel estimation
    • H04L25/024—Channel estimation channel estimation algorithms
    • H04L25/0242—Channel estimation channel estimation algorithms using matrix methods
    • H04L25/0246—Channel estimation channel estimation algorithms using matrix methods with factorisation

Abstract

1. Устройство для получения матрицы пространственного фильтра, содержащее: ! первый процессор, который во время работы получает матрицу отклика канала; и ! второй процессор, который во время работы итерационно получает первую матрицу на основе матрицы отклика канала и выводит матрицу пространственного фильтра на основе первой матрицы и матрицы отклика канала, при этом второй процессор рассчитывает обращение матрицы для матрицы, полученной от матрицы отклика канала, путем итерационного получения первой матрицы. ! 2. Устройство по п.1, в котором второй процессор во время работы инициализирует первую матрицу до единичной матрицы. ! 3. Устройство по п.1, в котором второй процессор во время работы для каждой из множества итераций получает промежуточный вектор строки на основе первой матрицы и вектора строки отклика канала, соответствующего строке матрицы отклика канала, для получения скалярной величины на основе промежуточного вектора строки и вектора строки отклика канала для получения промежуточной матрицы на основе промежуточного вектора строки и для обновления первой матрицы на основе скалярной величины и этой промежуточной матрицы. ! 4. Устройство по п.1, в котором первая матрица предназначена для получения матрицы пространственного фильтра с минимальной среднеквадратической ошибкой (MMSE). ! 5. Устройство по п.1, в котором второй процессор во время работы получает первую матрицу на основе следующего уравнения: ! ! где P i представляет собой первую матрицу для i-й итерации, h i представляет собой i-ю строку матрицы отклика канала, ri представляет собой скалярную величину, полученную на основе h i и P i-1, и "H" представ 1. A device for producing a spatial filter matrix, comprising:! the first processor, which during operation receives the channel response matrix; and! the second processor, which during operation iteratively obtains the first matrix based on the channel response matrix and outputs a spatial filter matrix based on the first matrix and the channel response matrix, while the second processor calculates the matrix inversion for the matrix obtained from the channel response matrix by iteratively obtaining the first matrices. ! 2. The device according to claim 1, in which the second processor during operation initializes the first matrix to a single matrix. ! 3. The device according to claim 1, in which the second processor during operation for each of the many iterations receives an intermediate row vector based on the first matrix and the channel response row vector corresponding to the channel response matrix row to obtain a scalar value based on the intermediate row vector and the channel response row vector to obtain an intermediate matrix based on the intermediate row vector and to update the first matrix based on the scalar value and this intermediate matrix. ! 4. The device according to claim 1, in which the first matrix is designed to obtain a spatial filter matrix with a minimum mean square error (MMSE). ! 5. The device according to claim 1, in which the second processor during operation receives the first matrix based on the following equation:! ! where P i is the first matrix for the i-th iteration, h i is the i-th row of the channel response matrix, ri is the scalar value obtained from h i and P i-1, and "H" is

Claims (13)

1. Устройство для получения матрицы пространственного фильтра, содержащее:1. A device for producing a spatial filter matrix, comprising: первый процессор, который во время работы получает матрицу отклика канала; иthe first processor, which during operation receives the channel response matrix; and второй процессор, который во время работы итерационно получает первую матрицу на основе матрицы отклика канала и выводит матрицу пространственного фильтра на основе первой матрицы и матрицы отклика канала, при этом второй процессор рассчитывает обращение матрицы для матрицы, полученной от матрицы отклика канала, путем итерационного получения первой матрицы.the second processor, which during operation iteratively obtains the first matrix based on the channel response matrix and outputs the spatial filter matrix based on the first matrix and the channel response matrix, while the second processor calculates the matrix inversion for the matrix obtained from the channel response matrix by iteratively obtaining the first matrices. 2. Устройство по п.1, в котором второй процессор во время работы инициализирует первую матрицу до единичной матрицы.2. The device according to claim 1, in which the second processor during operation initializes the first matrix to a single matrix. 3. Устройство по п.1, в котором второй процессор во время работы для каждой из множества итераций получает промежуточный вектор строки на основе первой матрицы и вектора строки отклика канала, соответствующего строке матрицы отклика канала, для получения скалярной величины на основе промежуточного вектора строки и вектора строки отклика канала для получения промежуточной матрицы на основе промежуточного вектора строки и для обновления первой матрицы на основе скалярной величины и этой промежуточной матрицы.3. The device according to claim 1, in which the second processor during operation for each of the many iterations receives an intermediate row vector based on the first matrix and the channel response row vector corresponding to the channel response matrix row to obtain a scalar value based on the intermediate row vector and the channel response row vector to obtain an intermediate matrix based on the intermediate row vector and to update the first matrix based on the scalar value and this intermediate matrix. 4. Устройство по п.1, в котором первая матрица предназначена для получения матрицы пространственного фильтра с минимальной среднеквадратической ошибкой (MMSE).4. The device according to claim 1, in which the first matrix is designed to obtain a spatial filter matrix with a minimum mean square error (MMSE). 5. Устройство по п.1, в котором второй процессор во время работы получает первую матрицу на основе следующего уравнения:5. The device according to claim 1, in which the second processor during operation receives the first matrix based on the following equation:
Figure 00000001
Figure 00000001
 где P i представляет собой первую матрицу для i-й итерации, h i представляет собой i-ю строку матрицы отклика канала, ri представляет собой скалярную величину, полученную на основе h i и P i-1, и "H" представляет собой сопряженную перестановку.where P i is the first matrix for the i-th iteration, h i is the i-th row of the channel response matrix, r i is the scalar value obtained from h i and P i-1 , and " H " is the conjugate rearrangement. 6. Устройство по п.1, в котором второй процессор во время работы получает первую матрицу на основе следующих уравнений:6. The device according to claim 1, in which the second processor during operation receives the first matrix based on the following equations:
Figure 00000002
Figure 00000002
Figure 00000003
Figure 00000003
 где P i представляет собой первую матрицу для i-й итерации, h i представляет собой i-ю строку матрицы отклика канала, a i представляет собой промежуточный вектор строки для i-й итерации, C i представляет собой промежуточную матрицу для i-й итерации, ri представляет собой скалярную величину для i-й итерации, δ2 n представляет собой дисперсию шума, и "H" представляет собой сопряженную перестановку.where P i represents the first matrix for the i-th iteration, h i represents the i-th row of the channel response matrix, a i represents the intermediate row vector for the i-iteration, C i represents the intermediate matrix for the i-iteration, r i represents the scalar quantity for the ith iteration, δ 2 n represents the variance of the noise, and “ H ” represents the conjugate permutation. 7. Устройство по п.1, в котором второй процессор во время работы получает матрицу пространственного фильтра на основе следующего уравнения:7. The device according to claim 1, in which the second processor during operation receives a spatial filter matrix based on the following equation:
Figure 00000004
Figure 00000004
 где М представляет собой матрицу пространственного фильтра, P представляет собой первую матрицу, H представляет собой матрицу отклика канала, и H представляет собой сопряженную перестановку.where M is a spatial filter matrix, P is a first matrix, H is a channel response matrix, and H is a conjugate permutation. 8. Способ получения матрицы пространственного фильтра, содержащий этапы, на которых:8. A method of obtaining a spatial filter matrix, comprising stages in which: итерационно получают первую матрицу на основе матрицы отклика канала, при этом обращение матрицы для матрицы, полученной от матрицы отклика канала, рассчитывают путем итерационного получения первой матрицы; иthe first matrix is iteratively obtained based on the channel response matrix, wherein the matrix inversion for the matrix obtained from the channel response matrix is calculated by iteratively obtaining the first matrix; and получают матрицу пространственного фильтра на основе первой матрицы и матрицы отклика канала.a spatial filter matrix is obtained based on the first matrix and the channel response matrix. 9. Способ по п.8, содержащий также этап, на котором инициализируют первую матрицу до единичной матрицы.9. The method of claim 8, further comprising initializing the first matrix to a single matrix. 10. Способ по п.8, в котором получение первой матрицы содержит, для каждой из множества итераций этапы, на которых10. The method of claim 8, wherein obtaining the first matrix comprises, for each of the many iterations, the steps of получают промежуточный вектор строки на основе первой матрицы и вектора строки отклика канала, соответствующего строке матрицы отклика канала,an intermediate row vector is obtained based on the first matrix and the channel response row vector corresponding to the channel response matrix row, получают скалярную величину на основе вектора промежуточной строки и вектора строки отклика канала,get a scalar value based on the intermediate line vector and the channel response line vector, получают промежуточную матрицу на основе промежуточного вектора строки, иreceive an intermediate matrix based on the intermediate row vector, and обновляют первую матрицу на основе скалярной величины и промежуточной матрицы.updating the first matrix based on the scalar value and the intermediate matrix. 11. Устройство для получения матрицы пространственного фильтра, содержащее:11. A device for producing a spatial filter matrix, comprising: средство итерационного получения первой матрицы на основе матрицы отклика канала, при этом обращение матрицы для матрицы, полученной от матрицы отклика канала, рассчитывают путем итерационного получения первой матрицы; иmeans for iteratively obtaining a first matrix based on a channel response matrix, wherein the matrix inversion for a matrix obtained from a channel response matrix is calculated by iteratively obtaining a first matrix; and средство получения матрицы пространственного фильтра на основе первой матрицы и матрицы отклика канала.means for obtaining a spatial filter matrix based on the first matrix and the channel response matrix. 12. Устройство по п.11, которое также содержит средство инициализации первой матрицы до единичной матрицы.12. The device according to claim 11, which also contains means for initializing the first matrix to a single matrix. 13. Устройство по п.11, в котором средство получения первой матрицы содержит для каждой из множества итераций,13. The device according to claim 11, in which the means for obtaining the first matrix contains for each of the many iterations, средство получения промежуточного вектора строки на основе первой матрицы и вектора строки отклика канала, соответствующего строке матрицы отклика канала,means for obtaining an intermediate row vector based on the first matrix and the channel response row vector corresponding to the channel response matrix row, средство получения скалярной величины на основе промежуточного вектора строки и вектора строки отклика канала,means for obtaining a scalar quantity based on an intermediate row vector and a channel response row vector, средство получения промежуточной матрицы на основе промежуточного вектора строки, иmeans for obtaining an intermediate matrix based on an intermediate row vector, and средство обновления первой матрицы на основе скалярной величины и промежуточной матрицы. means for updating the first matrix based on a scalar quantity and an intermediate matrix.
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Families Citing this family (49)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7366326B2 (en) * 2003-06-24 2008-04-29 University Of Maryland, Baltimore County Real-time implementation of field programmable gate arrays (FPGA) design in hyperspectral imaging
US8204149B2 (en) 2003-12-17 2012-06-19 Qualcomm Incorporated Spatial spreading in a multi-antenna communication system
US7336746B2 (en) 2004-12-09 2008-02-26 Qualcomm Incorporated Data transmission with spatial spreading in a MIMO communication system
US8169889B2 (en) 2004-02-18 2012-05-01 Qualcomm Incorporated Transmit diversity and spatial spreading for an OFDM-based multi-antenna communication system
US8923785B2 (en) 2004-05-07 2014-12-30 Qualcomm Incorporated Continuous beamforming for a MIMO-OFDM system
US8285226B2 (en) 2004-05-07 2012-10-09 Qualcomm Incorporated Steering diversity for an OFDM-based multi-antenna communication system
US7978649B2 (en) 2004-07-15 2011-07-12 Qualcomm, Incorporated Unified MIMO transmission and reception
US7711762B2 (en) * 2004-11-15 2010-05-04 Qualcomm Incorporated Efficient computation for eigenvalue decomposition and singular value decomposition of matrices
US7895254B2 (en) * 2004-11-15 2011-02-22 Qualcomm Incorporated Eigenvalue decomposition and singular value decomposition of matrices using Jacobi rotation
JP4429945B2 (en) * 2005-03-23 2010-03-10 株式会社エヌ・ティ・ティ・ドコモ MIMO multiplex communication apparatus and signal separation method
WO2006104142A1 (en) * 2005-03-28 2006-10-05 Nec Corporation Mimo decoder and mimo decoding method
US7602855B2 (en) * 2005-04-01 2009-10-13 Interdigital Technology Corporation Method and apparatus for singular value decomposition of a channel matrix
US8737494B2 (en) * 2006-01-09 2014-05-27 Broadcom Corporation Method and system for quantization for a general beamforming matrix in feedback information
US9025689B2 (en) 2005-07-20 2015-05-05 Stmicroelectronics S.R.L. Method and apparatus for multiple antenna communications, and related systems and computer program
EP1905182B1 (en) * 2005-07-20 2012-02-29 STMicroelectronics Srl Apparatus and method for detecting communications from multiple sources
TWI274482B (en) * 2005-10-18 2007-02-21 Ind Tech Res Inst MIMO-OFDM system and pre-coding and feedback method therein
US7818357B2 (en) * 2005-11-23 2010-10-19 Rambus Inc. Systems and methods for implementing CORDIC rotations for projectors and related operators
US8543070B2 (en) 2006-04-24 2013-09-24 Qualcomm Incorporated Reduced complexity beam-steered MIMO OFDM system
US8290089B2 (en) 2006-05-22 2012-10-16 Qualcomm Incorporated Derivation and feedback of transmit steering matrix
JP2008067308A (en) * 2006-09-11 2008-03-21 Fuji Xerox Co Ltd Color processing device, color processing method, and program
EP2119155A2 (en) * 2007-03-14 2009-11-18 STMicroelectronics S.r.l. A method and apparatus for multiple antenna communications, computer program product therefor
US7995457B2 (en) * 2007-04-16 2011-08-09 Broadcom Corporation Method and system for SFBC/STBC transmission of orthogonally coded signals with angle feedback in a diversity transmission system
US8457265B2 (en) * 2007-08-23 2013-06-04 Qualcomm Incorporated Method and apparatus for generating coefficients in a multi-input-multi-output (MIMO) system
KR101329012B1 (en) * 2007-10-11 2013-11-12 삼성전자주식회사 A multiple input multiple output receiver and method for detecting signal thereof
JP5122428B2 (en) * 2008-02-04 2013-01-16 株式会社エヌ・ティ・ティ・ドコモ Mobile communication system, receiving apparatus and method
US7986919B2 (en) * 2008-03-19 2011-07-26 Telefonaktiebolaget Lm Ericsson (Publ) Simplified impairments matrix calculation for SINR estimation
US8385439B2 (en) * 2008-05-27 2013-02-26 Nec Laboratories America, Inc. Polarization mode dispersion compensation in multilevel coded-modulation schemes using blast algorithm and iterative polarization cancellation
CN101621354B (en) * 2008-07-06 2013-07-31 财团法人工业技术研究院 Signal detecting method and receiver device using same
TWI381668B (en) * 2008-07-07 2013-01-01 Ind Tech Res Inst Signal detecting method and receiver using the same
US8488684B2 (en) 2008-09-17 2013-07-16 Qualcomm Incorporated Methods and systems for hybrid MIMO decoding
US8320510B2 (en) * 2008-09-17 2012-11-27 Qualcomm Incorporated MMSE MIMO decoder using QR decomposition
JP5389932B2 (en) * 2008-11-14 2014-01-15 エルジー エレクトロニクス インコーポレイティド Data transmission method and apparatus using multiple resources in multiple antenna system
KR100983126B1 (en) * 2008-12-22 2010-09-17 성균관대학교산학협력단 Apparatus and method for channel equalizing of ofdm
US8488724B2 (en) * 2009-05-14 2013-07-16 Silvus Technologies, Inc. Wideband interference mitigation for devices with multiple receivers
CN101909031B (en) * 2009-06-05 2013-06-26 北京信威通信技术股份有限公司 MMSE detection method for spread-spectrum OFDMA communication system
US8724746B2 (en) * 2011-03-17 2014-05-13 Futurewei Technologies, Inc. System and method for signaling and detecting in wireless communications systems
TW201322006A (en) * 2011-11-18 2013-06-01 Ind Tech Res Inst Data processing method and device using the same
KR101319795B1 (en) 2011-12-23 2013-10-17 삼성전기주식회사 Operation method of access point and wireless communication system using access point
CN102882579B (en) * 2012-09-24 2015-01-28 东南大学 Parallel matrix inversion method for multi-antenna system
EP2979410B1 (en) 2013-03-28 2018-04-25 Nokia Solutions and Networks Oy Channel estimation in wireless communications with beamforming
CN103532890B (en) * 2013-10-29 2017-03-29 东南大学 A kind of SVD decomposition methods to complex channel matrix
US20160036561A1 (en) * 2014-07-29 2016-02-04 MagnaCom Ltd. Orthogonal Frequency Division Multiplexing Based Communications Over Nonlinear Channels
US9485126B2 (en) * 2014-08-21 2016-11-01 The Boeing Company Signal combining system for constant envelope transmission of information
US9525470B1 (en) * 2015-10-19 2016-12-20 Xilinx, Inc. Adaptive multiple-input multiple-output (MIMO) data detection and precoding
CN106919537A (en) * 2017-03-07 2017-07-04 电子科技大学 A kind of efficient implementation method of the Jacobi conversion based on FPGA
WO2019141352A1 (en) * 2018-01-17 2019-07-25 Huawei Technologies Co., Ltd. Signal decoder and method for performing hermitian matrix inversion
CN108512581B (en) * 2018-03-01 2021-03-09 东南大学 Precoding recurrence method for large-scale MIMO (multiple input multiple output) increasing and decreasing antennas
CN109004965B (en) * 2018-07-26 2021-04-02 大连理工大学 Design method and device of hybrid beam forming filter based on millimeter wave MIMO system secure communication
CN112596701B (en) * 2021-03-05 2021-06-01 之江实验室 FPGA acceleration realization method based on unilateral Jacobian singular value decomposition

Family Cites Families (20)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6144711A (en) * 1996-08-29 2000-11-07 Cisco Systems, Inc. Spatio-temporal processing for communication
US6600796B1 (en) * 1999-11-12 2003-07-29 Lucent Technologies Inc. Method and apparatus for receiving wireless transmissions using multiple-antenna arrays
CA2360367C (en) * 1999-12-02 2007-02-06 Yu-Suk Yun Apparatus and method for transmitting and receiving data in a cdma communication system
US6987819B2 (en) * 2000-12-29 2006-01-17 Motorola, Inc. Method and device for multiple input/multiple output transmit and receive weights for equal-rate data streams
US20030012315A1 (en) * 2001-07-06 2003-01-16 John Fan System and method for multistage error correction coding wirelessly transmitted information in a multiple antennae communication system
US20030125040A1 (en) * 2001-11-06 2003-07-03 Walton Jay R. Multiple-access multiple-input multiple-output (MIMO) communication system
DE60206873T2 (en) * 2002-02-14 2006-06-14 Lucent Technologies Inc Receiver and method for multiple input and multiple output iterative detection by feedback of soft decisions
US7076263B2 (en) * 2002-02-19 2006-07-11 Qualcomm, Incorporated Power control for partial channel-state information (CSI) multiple-input, multiple-output (MIMO) systems
US6636568B2 (en) * 2002-03-01 2003-10-21 Qualcomm Data transmission with non-uniform distribution of data rates for a multiple-input multiple-output (MIMO) system
AU2003219882A1 (en) * 2002-03-01 2003-09-16 Cognio, Inc. System and method for joint maximal ratio combining
US6801580B2 (en) * 2002-04-09 2004-10-05 Qualcomm, Incorporated Ordered successive interference cancellation receiver processing for multipath channels
US6757321B2 (en) * 2002-05-22 2004-06-29 Interdigital Technology Corporation Segment-wise channel equalization based data estimation
US7613248B2 (en) * 2002-06-24 2009-11-03 Qualcomm Incorporated Signal processing with channel eigenmode decomposition and channel inversion for MIMO systems
US7254192B2 (en) * 2002-07-12 2007-08-07 Texas Instruments Incorporated Iterative detection in MIMO systems
US8208364B2 (en) * 2002-10-25 2012-06-26 Qualcomm Incorporated MIMO system with multiple spatial multiplexing modes
US7742546B2 (en) * 2003-10-08 2010-06-22 Qualcomm Incorporated Receiver spatial processing for eigenmode transmission in a MIMO system
CN1281003C (en) * 2004-02-26 2006-10-18 上海交通大学 Time-domain adaptive channel estimating method based on pilot matrix
US7593489B2 (en) * 2005-03-14 2009-09-22 Koshy John C Iterative STBICM MIMO receiver using group-wise demapping
US7602855B2 (en) * 2005-04-01 2009-10-13 Interdigital Technology Corporation Method and apparatus for singular value decomposition of a channel matrix
EP1878206A4 (en) * 2005-04-25 2012-12-19 Xocyst Transfer Ag L L C Beamforming systems and methods

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